1. CS 414 - Spring 2014 CS 414 – Multimedia Systems Design Lecture 35 – Media Server (Part 4) Klara Nahrstedt Spring 2014

2. Administrative MP3 going on CS 414 - Spring 2014

3. Covered Aspects of Multimedia Image/Video Capture Media Server Storage Transmission Compression Processing Audio/Video Presentation Playback Audio/Video Perception/ Playback Audio Information Representation Transmission Audio Capture A/V Playback Image/Video Information Representation CS 414 - Spring 2014

4. Media Server Architecture CS 414 - Spring 2014 Storage device Disk controller Storage management File System Memory Management (MaxBuf, MinBuf Policy Buffering) Content Distribution (Caching, Patching, Batching) Network Attachment (RTP/RTCP, ….) Incoming request Delivered data

5. Outline Multimedia File Server/System Organization Example of Early Media Server – Medusa Example of Multimedia File System – Symphony Example of Industrial Multimedia File System – Google File System CS 414 - Spring 2014

6. Constant and Real-time Retrieval of MM Data Retrieve index in real-time Retrieve block information from FAT Retrieve data from disk in real-time Real-time playback  Implement linked list Random seek (Fast Forward, Rewind)  Implement indexing MM File Maps  include metadata about MM objects: creator of video, sync info CS 414 - Spring 2014

7. Fast Forward and Rewind (Implementation) Play back media at higher rate  Not practical solution Continue playback at normal rate, but skip frames  Define skip steps, e.g. skip every 3 rd, or 5 th frame  Be careful about interdependencies within MPEG frames Approaches for FF:  Create a separate and highly compressed file  Categorize each frame as relevant or irrelevant  Intelligent arrangement of blocks for FF CS 414 - Spring 2014

8. Block Size Issues in File Organization Small Block Sizes  Use smaller block sizes, smaller than average frame size Organization Strategy: Constant Time Length Need Metadata structure, called Frame Index  Frame means a time frame within a movie  Under the time frame read all blocks (audio, video, text) belonging to this time frame CS 414 - Spring 2014 AV VT Frame index Movie Time line AV VT ……… V A V

9. Block Size Issues Large Block Size  Use large blocks (e.g., 256 KB) which include multiple audio/video/text frames Organization Strategy: Constant Data Length Need Metadata structure, called Block Index  Each block contains multiple movie frames CS 414 - Spring 2014 AV V V AAA V VV Block Index

10. Tradeoffs Frame index : needs large RAM usage while movie is playing, however little disk wastage Block index (if frames are not split across blocks): need low RAM usage, but major disk wastage – internal disk fragmentation Block index(if frames are split across blocks): need low Ram usage, no disk wastage, extra seek times CS 414 - Spring 2014

11. Source: Medusa (Parallel Video Servers), Hai Jin, 2004 Example of Media Server Architecture

12. Example Multimedia File System (Symphony) CS 414 - Spring 2014 Source: P. Shenoy et al, “Symphony: An Integrated Multimedia File System”, SPIE/ACM MMCN 1998 System out of UT Austin Symphony’s Goals:  Support real-time and non-real time request  Support multiple block sizes and control over their placement  Support variety of fault-tolerance techniques  Provide two level metadata structure that all type- specific information can be supported

13. Design Decisions CS 414 - Spring 2014

14. Two Level Symphony Architecture CS 414 - Spring 2014 Resource Manager: Disk Schedule System (called Cello) that uses modified SCAN-EDF for RT Requests and C-SCAN for non-RT requests as long as deadlines are not violated Admission Control and Resource Reservation for scheduling

15. Disk Subsystem Architecture CS 414 - Spring 2014 Service Manager : supports mechanisms for efficient scheduling of best-effort, aperiodic real-time and periodic real-time requests Storage Manager: supports mechanisms for allocation and de-allocation of blocks Of different sizes and controlling data placement on the disk Fault Tolerance layer: enables multiple data type specific failure recovery techniques Metadata Manager: enables data types specific structure to be assigned to files

16. Cello Disk Scheduling Framework CS 414 - Spring 2014 Source: Prashant Shenoy, 2001

17. Class-Independent Scheduler CS 414 - Spring 2014 Source: Prashant Shenoy, 2001

18. Class-Specific Schedulers CS 414 - Spring 2014

19. Validation: Symphony’s scheduling system (Cello) CS 414 - Spring 2014 Source: Shenoy Prashant, 2001

20. Buffer Subsystem Enable multiple data types specific caching policies to coexist Partition cache among various data types and allow each caching policy to independently manage its partition Maintain two buffer pools:  a pool of de-allocated buffers  pool of cached buffers. Cache pool is further partitioned among various caching policies Examples of caching policies for each cache buffer: LRU, MRU. CS 414 - Spring 2014

21. Buffer Subsystem (Protocol) Receive buffer allocation request Check if the requested block is cached.  If yes, it returns the requested block  If cache miss, allocate buffer from the pool of de-allocated buffers and insert this buffer into the appropriate cache partition Determine (Caching policy that manages individual cache) position in the buffer cache  If pool of de-allocated buffers falls below low watermark, buffers are evicted from cache and returned to de-allocated pool  Use TTR (Time-To- Reaccess) values to determine victims TTR – estimate of next time at which the buffer is likely to be accessed CS 414 - Spring 2014

22. Video Module Implements policies for placement, retrieval, metadata management and caching of video data Placement of video files on disk arrays is governed by two parameters: block size and striping policy.  supports both fixed size blocks (fixed number of bytes) and variable size blocks (fixed number of frames)  uses location hints so as to minimize seek and rotational latency overheads Retrieval Policy:  supports periodic RT requests (server push mode) and aperiodic RT requests (client pull mode) CS 414 - Spring 2014

23. Video Module (Metadata Management) To allow efficient random access at byte level and frame level, video module maintains two-level index structure  First level of index, referred to as frame map, maps frame offset to byte offset  Second level, referred to as byte map, maps byte offset to disk block locations CS 414 - Spring 2014

24. Google File System (Big Table) Wikipedia:GFS

25. Google File System Files divided into fixed size big chunks of 64 Mbytes Chunk servers Files are usually appended to or read Run on cheap commodity computers High failure rate High data throughputs and cost of latency Two types of nodes  Master node and large number of chunk servers. Designed for system-to-system interaction The Google File System: Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung, Google, SOSP '03

26. Big Table High-performance data storage system Built on top of  Google File System  Chubby Lock Service  SSTable (log-structured storage) Supports systems such as  MapReduce  YouTube  Google Earth  Google Maps  Gmail

27. Spanner Successor to Big Table Globally distributed relational database management system (RDBMS) Google F1 – built on top of Spanner (replaces MySQL) Corbett, James C; Dean, Jeffrey; Epstein, Michael; Fikes, Andrew; Frost, Christopher; Furman, JJ; Ghemawat, Sanjay; Gubarev, Andrey; Heiser, Christopher; Hochschild, Peter; Hsieh, Wilson; Kanthak, Sebastian; Kogan, Eugene; Li, Hongyi; Lloyd, Alexander; Melnik, Sergey; Mwaura, David; Nagle, David; Quinlan, Sean; Rao, Rajesh; Rolig, Lindsay; Saito, Yasushi; Szymaniak, Michal; Taylor, Christopher; Wang, Ruth; Woodford, Dale, "Spanner: Google’s Globally-Distributed Database", Proceedings of OSDI 2012 (Google), retrieved 18 September 2012."Spanner: Google’s Globally-Distributed Database"

28. Conclusion The data placement, scheduling, block size decisions, caching, concurrent clients support, buffering, are very important for any media server design and implementation. Huge explosion in media storage-cloud storage  Similar software – Apache Cassandra, Hadoop, Hypertable, Apache Accumulo, Apache Hbase, … Next Lecture – we discuss P2P Streaming CS 414 - Spring 2014

29. Symphony Caching Policy Interval-based caching for video module LRU caching for text module CS 414 - Spring 2014